Papers
Topics
Authors
Recent
AI Research Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 81 tok/s
Gemini 2.5 Pro 42 tok/s Pro
GPT-5 Medium 23 tok/s Pro
GPT-5 High 20 tok/s Pro
GPT-4o 103 tok/s Pro
Kimi K2 188 tok/s Pro
GPT OSS 120B 454 tok/s Pro
Claude Sonnet 4 38 tok/s Pro
2000 character limit reached

3D tracking the Brownian motion of colloidal particles using digital holographic microscopy and joint reconstruction (1506.06615v1)

Published 19 Jun 2015 in physics.ins-det and physics.optics

Abstract: In-line digital holography is a valuable tool for sizing, locating and tracking micro- or nano-objects in a volume. When a parametric imaging model is available, Inverse Problems approaches provide a straightforward estimate of the object parameters by fitting data with the model, thereby allowing accurate reconstruction. As recently proposed and demonstrated, combining pixel super-resolution techniques with Inverse Problems approaches improves the estimation of particle size and 3D-position. Here we demonstrate the accurate tracking of colloidal particles in Brownian motion. Particle size and 3D-position are jointly optimized from video holograms acquired with a digital holographic microscopy set up based on a "low-end" microscope objective ($\times 20$, $\rm NA\ 0.5$). Exploiting information redundancy makes it possible to characterize particles with a standard deviation of 15 nm in size and a theoretical resolution of 2 x 2 x 5 nm$3$ for position under additive white Gaussian noise assumption.

Summary

We haven't generated a summary for this paper yet.

Lightbulb On Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.